About The Position

The Vice President, Systems Engineering role at Goldman Sachs Services LLC in Dallas, Texas involves applying expertise across all Engineering disciplines, including datacenter design, networks, storage, grid compute, operating systems, databases, communications, market data, and software languages. The position oversees the design and build-out of the firm’s computer and data infrastructure, including identifying internal hardware and implementing public and private cloud-based solutions for seamless on-demand scaling of applications. Responsibilities include overseeing the creation of automated testing processes, standards, solutions, and tools to ensure smooth business operations. The role also involves leveraging data mining and machine learning expertise to identify and react to infrastructure and platform problems, overseeing the identification, analysis, and resolution of application issues by documenting repetitive error resolutions and minimizing operational errors. The position tracks and manages application health and ensures application service performance, manages risk and cost in the production environment and change management process, and improves application stability and performance by automating failures using machine learning techniques and analyzing discrepancies and trends. Additionally, the role manages production incidents and communicates with users, application owners, vendors, and stakeholders, develops sustainable systems and services through automation, performance tuning, and database queries, and manages business continuity planning and disaster recovery, including planning appropriate contingency plans.

Requirements

  • Master’s degree (U.S. or foreign equivalent) in Computer Science, Computer Engineering, Information Systems/Technology, or related field and three (3) years of experience in job offered or a related Systems Engineering role OR Bachelor’s degree (U.S. or foreign equivalent) in Computer Science, Computer Engineering, Information Systems/Technology, or related field and five (5) years of experience in job offered or a related Systems Engineering role.
  • Prior work experience must include three (3) years (with a Master’s degree) OR five (5) years (with a Bachelor’s degree) with 4 of the 6 following skills: performance tuning and troubleshooting application issues utilizing Oracle, code debugging, or log analysis; software development using UNIX operating system, Shell scripting, or Python; designing and supporting database systems utilizing technologies such as DB2 or Sybase ASE; working with the full Software Development Life Cycle (SDLC) including requirements gathering, design, prioritization, coding testing, release, and support; SQL performance, tuning, and diagnosing potential performance issues by analyzing query execution plans and setting up disaster recovery; and performing systems management for Windows platforms such as Microsoft Configuration Manager or comparable enterprise systems management products.

Responsibilities

  • Apply expertise across all Engineering, including datacenter design, networks, storage, grid compute, operating systems, databases, communications, market data and software languages.
  • Oversee the design and build out of the firm’s computer and data infrastructure, including identification of internal hardware and implementation of public and private cloud-based solutions to provide seamless on-demand scaling of the firm's applications.
  • Oversee the creation of automated testing processes, standards, solutions and tools to ensure smooth operation of the firm’s businesses.
  • Leverage data mining and machine learning expertise to identify and react to problems in the firm’s infrastructure and platforms.
  • Oversee the identification, analysis, and resolution of application issues by documenting repetitive error resolutions and minimizing operational errors.
  • Track and manage application health and ensure application service performance.
  • Manage risk and cost in the production environment and change management process.
  • Improve application stability and performance by automating failures using machine learning techniques and analyzing discrepancies and trends.
  • Manage production incidents and communicate with users, applications owners, vendors, and internal and external stakeholders.
  • Develop sustainable systems and services through automation, performance tuning and database queries.
  • Manage business continuity planning and disaster recovery, and plan appropriate contingency plans.
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